Nowadays, search engines have become indispensable parts of modern human life, which create hundreds and thousands of search logs every second throughout the world. With explosive growth of online information, a key issue for web search service is to better understand user's needs through short search queries to match the user preference as much as possible. The search engines play an important role in human life, and they have greatly facilitated people's daily lives through providing information to the user.
However, it may be difficult for machines to understand what people are looking for. Due to lack of personal information in some scenarios and huge calculation required when seeking for a relevant user group, a personalized search becomes a challenging problem. Different people may have different interests. Even for a single user, the user's interest may change over time. Thus, it may be necessary for online search services to meet the need of personalized searching and to adapt to the change of user intent over time. As a result, user specific information (e.g. user profile, user query history, previous view content information, etc.) becomes significant for identifying the user's interest.
The disclosed methods and systems are directed to solve one or more problems set forth above and other problems.